Senior AI Solutions Architect Lead is needed to support the delivery, enhancement, and adoption of enterprise data and analytics products used across multiple DoD organizations. The ideal candidate will have experience in systems engineering and AI/ML architectures, and will lead a team of 8-15 direct reports.
Requirements
- Active Top Secret (TS) clearance with SCI eligibility.
- Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or related technical discipline and 8–12 years of relevant experience OR Master’s degree in a related field and 6–10 years of relevant experience.
- Minimum of 10 years of experience in systems engineering and AI and/or data intelligence architectures.
- Experience architecting and deploying enterprise AI/ML solutions in cloud environments (AWS, Azure, or GCP).
- Experience designing and delivering AI/ML solutions in enterprise cloud environments (AWS, Azure, or GCP).
- Experience integrating AI/ML capabilities into production systems using APIs and microservices architectures.
- Experience developing AI/ML pipelines including data preparation, model training, validation, and deployment.
- Experience working across cross-functional teams to deliver integrated technical solutions.
- Experience operating within SAFe or large-scale Agile frameworks supporting enterprise systems.
- Experience with system architecture design and implementation in classified environments.
- Experience developing Agentic AI solutions such as autonomous planning–execution–reflection loops, multi-agent collaboration and coordination, and tool usage patterns including API integration, retrieval-augmented generation (RAG), and memory/context management)
- Experience using vector databases (e.g., Pinecone, Weaviate, FAISS)
- Demonstrated experience leading and mentoring technical engineering teams.
- Strong understanding of AI/ML technologies and their application in enterprise environments.
- Strong understanding of AI/ML frameworks (e.g., PyTorch, TensorFlow) and data engineering concepts.
- Solid understanding and hands-on experience with generative AI models such as prompt engineering, chain-of-thought reasoning, and Natural Language Processing (NLP) tasks such as entity extraction, summarization, and semantic search.
- Working knowledge of Large Language Models (LLMs) and agent frameworks such as LangChain, LangGraph, CrewAI, A2A, MCP, or AutoGen
Benefits
- Generous Paid Time Off
- 401k Matching
- Retirement Plan
